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Genetic Algorithms and Genetic Programming in Computational Finance

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Cover of 'Genetic Algorithms and Genetic Programming in Computational Finance'

Table of Contents

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    Book Overview
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    Chapter 1 Genetic Algorithms and Genetic Programming in Computational Finance: An Overview of the Book
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    Chapter 2 Genetic Algorithms In Economics and Finance: Forecasting Stock Market Prices And Foreign Exchange — A Review
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    Chapter 3 Genetic Programming: A Tutorial With The Software Simple GP
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    Chapter 4 GP and the Predictive Power of Internet Message Traffic
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    Chapter 5 Genetic Programming of Polynomial Models for Financial Forecasting
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    Chapter 6 NXCS: Hybrid Approach to Stock Indexes Forecasting
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    Chapter 7 Eddie for Financial Forecasting
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    Chapter 8 Forecasting Market Indices Using Evolutionary Automatic Programming
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    Chapter 9 Genetic Fuzzy Expert Trading System for Nasdaq Stock Market Timing
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    Chapter 10 Portfolio Selection and Management Using a Hybrid Intelligent and Statistical System
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    Chapter 11 Intelligent Cash Flow: Planning and Optimization Using Genetic Algorithms
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    Chapter 12 The Self-Evolving Logic of Financial Claim Prices
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    Chapter 13 Using a Genetic Program to Predict Exchange Rate Volatility
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    Chapter 14 Evolutionary Decision Trees for Stock Index Options and Futures Arbitrage
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    Chapter 15 A Model of Boundedly Rational Consumer Choice
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    Chapter 16 Price Discovery in Agent-Based Computational Modeling of the Artificial Stock Market
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    Chapter 17 Individual Rationality as a Partial Impediment to Market Efficiency
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    Chapter 18 A Numerical Study on the Evolution of Portfolio Rules
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    Chapter 19 Adaptive Portfolio Managers in Stock Markets: An Approach Using Genetic Algorithms
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    Chapter 20 Learning and Convergence to Pareto Optimality
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    Chapter 21 The New Evolutionary Computational Paradigm of Complex Adaptive Systems
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Title
Genetic Algorithms and Genetic Programming in Computational Finance
Published by
Springer US, July 2002
DOI 10.1007/978-1-4615-0835-9
ISBNs
978-0-7923-7601-9, 978-1-4613-5262-4, 978-1-4615-0835-9
Editors

Shu-Heng Chen

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
France 1 1%
Germany 1 1%
Italy 1 1%
Estonia 1 1%
Unknown 69 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 27%
Student > Master 15 20%
Researcher 7 9%
Student > Bachelor 4 5%
Professor 4 5%
Other 11 15%
Unknown 14 19%
Readers by discipline Count As %
Computer Science 28 37%
Economics, Econometrics and Finance 9 12%
Engineering 6 8%
Business, Management and Accounting 4 5%
Physics and Astronomy 2 3%
Other 10 13%
Unknown 16 21%